Research on spatial pattern of passenger flow in rail transit based on fixed time interval

The distribution law of passenger flow in rail transit can improve the accuracy and precision of passenger flow forecasting, and provide theoretical support for the operation of passenger flow in rail transit, management and travel. Therefore, the time series data of passenger flow is reshaped; that is, the data of passenger flow are converted into three attributes: day, time interval (week/month) and passenger flow, and the spatial patterns of passenger flow at a fixed time interval are analysed to reveal the periodic fluctuation trend of passenger flow. Different distribution models are established based on the data of passenger flow, comparing the errors and fitting effects of different distribution models to obtain the distribution law of passenger flow; Harbin Metro Line 1 is taken as an example. The results show that the fluctuation trend of passenger flow can be observed more intuitively after adding the attribution of time interval. The variation of passenger flow at different stations with weekly intervals has the same fluctuation law and presents Gaussian distribution; the particularity of sudden changes in passenger flow caused by holidays is taken into account, and the fluctuation trend of passenger flow in different weeks can be more intuitively observed.